Comprehensive Summary
This article reviews the use of generative AI, particularly large language models, in otolaryngology (ENT) practice. Applications include medical education, patient communication, diagnostics, and clinical decision support. AI systems performed well for structured tasks such as explaining medical concepts or drafting materials but struggled with complex reasoning and sometimes produced inaccurate or “hallucinated” outputs. The authors conclude that while AI holds promise in ENT medicine, its usefulness depends on rigorous validation and careful integration into clinical practice.
Outcomes and Implications
This research matters because AI could help doctors save time, teach students, and communicate more clearly with patients. If used carefully, it might also support diagnosis and decision making in ENT, though it is not yet reliable enough to replace clinical judgment. In the near future, we may see AI tools being used in small ways such as helping write reports or explain treatment options while bigger roles like guiding diagnoses or therapies will take more years of testing and regulation. Overall, the article shows that AI has exciting potential, but its clinical use in ENT will depend on proving it can be safe, accurate, and trustworthy.